1. Field of the Invention
The present invention relates to an image processing method and an image processing system for extracting a temporal change in a subject based on images such as X-ray images of the subject.
2. Description of the Related Art
In the field of medical image technology, intensive research activities continue to occur on computer aided diagnosis (CAD). In CAD, a diseased part of a patient is detected by analyzing a diagnosis image such as an X-ray image or a CT (Computer Tomography) image using a computer. CAD is a promising technique for early disease detection.
A wide variety of CAD techniques have been proposed depending on what is detected and on what type of image is output. Of the wide variety of techniques, one promising technique is known as temporal difference CAD. In this technique, a difference between images of the same subject taken at different times is detected, and an image is produced based on the detected difference such that a part having a temporal difference is enhanced in the image.
More specifically, in the temporal difference CAD, for example, when a set of chest X-ray images (a current image and a past image) taken at different times is given, images are analyzed to detect the relative positional displacement between the images. The positional displacement of the current image or the past image is corrected such that the anatomical parts of the two images come to the same positions. Thereafter, the difference between the two images is detected on a pixel-by-pixel basis, and a difference image indicating the difference is produced. Because the temporal difference CAD technique provides a difference image that indicates only a temporal difference between images taken at different times without indicating the anatomically normal parts, the temporal difference CAD technique is very useful to monitor a change in a diseased part.
An example of a temporal difference CAD technique is disclosed in U.S. Pat. No. 5,982,915. FIG. 7 shows a process of determining a temporal difference in accordance with the technique disclosed in U.S. Pat. No. 5,982,915.
In the technique shown in FIG. 7, in step P1, a current image and past image captured prior to the current image each have a 2048×2048 resolution. The images are converted to images with lower resolutions of 512×512 and 128×128 by using a proper resolution conversion method. In step P2, the images with the 128×128 resolution are passed through a Gaussian filter to remove high-frequency components from the images thereby producing images with a reduced size representing their outline.
A global shift vector indicating a global positional replacement between two reduced images with the 128×128 resolution is then determined. In step P4, based on the positional relationship between the two images indicated by the global shift vector, regions of interest (ROIs) are set in each image with the 512×512 resolution, and local shift vectors are determined by comparing each pair of corresponding ROIs of the two images. Parameters that allow calculation of a shift vector at an arbitrary position are determined by means of interpolation using a two-dimensional polynomial, and the relative positional displacement between the two images is corrected by modifying the current image or the past image. Thereafter, the difference between the two images is detected and a difference image is produced based on the detected difference.
As described above, a high-accuracy positional correction is made by performing the two-stage correction process, that is, by first correcting the positional displacement due to a difference in position of a subject whose image is taken, and then correcting the global displacement using reduced images before performing the difference detection process.
In principle, the difference image indicates only the difference between two images. This means that when each image includes a diseased part, if there is no change in the diseased part between the two images, the difference image indicates nothing about the diseased part. This can cause wrong diagnosis unless information is provided to indicate that there is the diseased part.
If a diseased part has already been detected, when a difference image is produced to monitor a change in the diseased part, it is desirable that the difference image produced via the difference determination process precisely represents the details of the difference in the diseased part.
However, in the conventional technique, past diagnosis information of a patient is not used in the temporal difference determination process, which can cause a reduction in reliability of diagnosis. Thus, there is a need for a technique to avoid such a problem.